Particle filters for positioning, navigation, and tracking
Particle filters for positioning, navigation, and tracking
复制标题
DOI：
10.1109/78.978396
复制
发表时间：
2002-02-01
影响因子：
5.4
通讯作者：
Nordlund, PJ
中科院分区：
文献类型：
--
作者：
Gustafsson, F;Gunnarsson, F;Nordlund, PJ
定位，导航和跟踪问题，使用粒子滤波器（顺序蒙特卡罗方法）的框架。它由一类运动模型和一般的位置非线性测量方程组成。提出了一种通用算法，该算法对粒子维数要求很低。它基于边缘化，使卡尔曼滤波器能够估计所有位置导数，并且粒子滤波器变得低维。这对于高性能的实时应用是至关重要的。汽车和机载应用的数值说明了优于经典的卡尔曼滤波算法。在这里，非线性模型和非高斯噪声的使用是提高精度的主要原因。更具体地说，我们描述了如何使用地图匹配技术来匹配飞机的高程剖面到数字高程地图和汽车的水平行驶路径到街道地图。在这两种情况下，实时实施是可用的，测试表明，在这两种情况下的精度与卫星导航（如GPS）相当，但具有更高的完整性。基于模拟，我们还认为粒子滤波器可以用于定位的基础上，手机测量，在飞机上的组合导航，并在飞机和汽车的目标跟踪。最后，粒子滤波器使一个有前途的解决方案，导航和跟踪的组合任务，可能应用于空中狩猎和防撞系统中的汽车。
A framework for positioning, navigation, and tracking problems using particle filters (sequential Monte Carlo methods) is developed. It consists of a class of motion models and a general nonlinear measurement equation in position. A general algorithm is presented, which is parsimonious with the particle dimension. It is based on marginalization, enabling a Kalman filter to estimate all position derivatives, and the particle filter becomes low dimensional. This is of utmost importance for high-performance real-time applications.Automotive and airborne applications illustrate numerically the advantage over classical Kalman filter-based algorithms. Here, the use of nonlinear models and non-Gaussian noise is the main explanation for the improvement in accuracy.More specifically, we describe how the technique of map matching is used to match an aircraft's elevation profile to a digital elevation map and a car's horizontal driven path to a street map. In both cases, real-time implementations are available, and tests have shown that the accuracy in both cases is comparable with satellite navigation (as GPS) but with higher integrity. Based on simulations, we also argue how the particle filter can be used for positioning based on cellular phone measurements, for integrated navigation in aircraft, and for target tracking in aircraft and cars. Finally, the particle filter enables a promising solution to the combined task of navigation and tracking, with possible application to airborne hunting and collision avoidance systems in cars.